The AI and analytics fields are multidisciplinary and rapidly evolving, reason why a broad technical knowledge is a must. From cloud technologies to recurrent neural networks for natural language processing, every subfield requires meticulous attention.
Descriptive, predictive, and prescriptive analytics are powered by statistical analysis. Business intelligence consists in analyzing business data to extract actionable insights. Analytics and BI are the main engine of every serious business strategy.
A step further than analytics, machine learning uses bleeding edge artificial intelligence algorithms to solve complex business problems, some of them were previously thought unsolvable.
Cloud technologies have revolutionized the data business, perhaps more than any other. Everyone now has access to unlimited storage and computing ressources at low rates. Cloud clients can pay for only the ressources they used, for the time they used them, to a fraction of a second.
One of the major AI advances is the ability of machines to understand text. Natural language processing opens countless applications like sentiment analysis and topic classification. With sentiment analysis, you can for example analyze if social media mentions are favorable or unfavorable and compile a reputation index.
Stocks, sales, number of patients in an ER room per day, all have in common the fact that they are quantities that varie over time. Times series analysis is the art of extracting information like seasonality, or trends, from such series. Forecasting future trends also relies on these techniques.
Skillfull visual representation of data can make complicated trends understood at a glance. Data visualizations are by far the most persuasive tool to non-experts. These visualizations can be integrated in a web interface and updated in real time and be used to monitor data continuously, these are called dashboards.